ZHU, Lei - HKUST Class Schedule & Quota

Class Schedule & Quota
2026-27 Fall 2025-26 Summer 2025-26 Spring 2025-26 Winter
2026-27 Fall
Common Core Course
The class information on this page will normally be updated every 15 to 20 minutes during class enrollment period.
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AIAA AMAT BSBE CMAA CNCC CNGF DLED DSAA EOAS FTEC FUNH INFH INTR IOTA IPEN LANG MICS MSSM PDEV PLED ROAS SEEN SMMG SOCH SYSH UCMP UCUG UFUG UGOD

COURSE INFO

DESCRIPTION	This course aims at guiding undergraduate students of the ROAS major for their academic path and future. This course is mostly introductory and is proposed to inspire UG students for their academic path development and growth of maturity in four years of UG study. Activities may include seminars, workshops, advising and sharing sessions, interaction with faculty and teaching staff, and discussion with student peers or alumni. Grading type: Pass/ Fail

DESCRIPTION

This course aims at guiding undergraduate students of the ROAS major for their academic path and future. This course is mostly introductory and is proposed to inspire UG students for their academic path development and growth of maturity in four years of UG study. Activities may include seminars, workshops, advising and sharing sessions, interaction with faculty and teaching staff, and discussion with student peers or alumni. Grading type: Pass/ Fail

ROAS 1010 - Introduction to Robotics and Autonomous Systems (1 unit)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6514)	01-SEP-2026 - 28-NOV-2026 We 10:30AM - 11:50AM	Rm 201, W2	DING, Fangqiang HUANG, Qiang JI, Yiding LI, Haoang MA, Jun NIE, Qiang SONG, Jie YANG, Jun YASA, Immihan Ceren YASA, Oncay ZHAO, Hang ZHU, Lei	40	0	40	0

COURSE INFO

PREVIOUS CODE	ROAS 6000B
DESCRIPTION	Light traveling in the 3D world interacts with the scene through intricate processes before being captured by a camera. These processes result in the dazzling effects like color and shading, complex surface and material appearance, different weathering, just to name a few. Physics based vision aims to invert the processes to recover the scene properties, such as shape, reflectance, light distribution, medium properties, etc., from the images by modelling and analyzing the imaging process to extract desired features or information. This course introduces the advanced methodologies in the context of physical-based vision for robotics and autonomous systems. We will introduce diverse techniques, covering from traditional methods based on hand-crafted features to recent deep learning methods. Apart from the fundamental knowledge in physical-based vision, the students will also have opportunities to discover and learn cutting-edge methodologies in popular physical-based vision topics (i.e., bad-weather restoration, shadow detection and removal, specular highlight detection and removal, intrinsic image decomposition, reflection detection and removal, and so on) of the physical-based vision, aligning with the substantial developments in robotics, autonomous driving, UAVs, etc.

PREVIOUS CODE

ROAS 6000B

DESCRIPTION

Light traveling in the 3D world interacts with the scene through intricate processes before being captured by a camera. These processes result in the dazzling effects like color and shading, complex surface and material appearance, different weathering, just to name a few. Physics based vision aims to invert the processes to recover the scene properties, such as shape, reflectance, light distribution, medium properties, etc., from the images by modelling and analyzing the imaging process to extract desired features or information. This course introduces the advanced methodologies in the context of physical-based vision for robotics and autonomous systems. We will introduce diverse techniques, covering from traditional methods based on hand-crafted features to recent deep learning methods. Apart from the fundamental knowledge in physical-based vision, the students will also have opportunities to discover and learn cutting-edge methodologies in popular physical-based vision topics (i.e., bad-weather restoration, shadow detection and removal, specular highlight detection and removal, intrinsic image decomposition, reflection detection and removal, and so on) of the physical-based vision, aligning with the substantial developments in robotics, autonomous driving, UAVs, etc.

ROAS 5800 - Physical-based Vision for Robot and Autonomous Driving (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6245)	Tu 03:00PM - 05:50PM	Rm 202, W4	ZHU, Lei	40 Quota/Enrol/Avail PhD(ROAS): 20/0/20	0	40	0